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Monday, August 31, 2015

Apaper just published in Science by the "Open Science Collaboration" reports the results of a multi-year multi-institution effort to replicate 100 psychology studies published in three top psychology journals in 2008. This effort has often been discussed since it began in 2011, in large part because the importance of replicability in confirming scientific results is integral to the 'scientific method,' but replicability studies aren't a terribly creative use of a researcher's time, and they're difficult to publish so they aren't often on researchers' To-Do lists. So, this was unusual.

There are many reasons a study can't be replicated. Sometimes the study was poorly conceived or carried out (assumptions and biases not taken into account), sometimes the results pertain only to the particular sample reported (a single family or population), sometimes the methods in an original study aren't described well enough to be replicated, sometimes random or even systematic error (instrument behaving badly) skews the results.

Because there's no such thing as a perfect study, replication studies can be victims of any of the same issues, so interpreting lack of replication isn't necessarily straightforward, and certainly doesn't always mean that the original study was flawed.

The Open Science Collaboration was scrupulous in its efforts to replicate original studies as carefully and faithfully as possible. Still, the results weren't pretty. The authors write:

Replication effects were half the magnitude of original effects, representing a substantial decline. Ninety-seven percent of original studies had statistically significant results. Thirty-six percent of replications had statistically significant results; 47% of original effect sizes were in the 95% confidence interval of the replication effect size; 39% of effects were subjectively rated to have replicated the original result; and if no bias in original results is assumed, combining original and replication results left 68% with statistically significant effects.

Interestingly enough, the authors aren't quite sure what any of this means. First, as they point out, direct replication doesn't verify the theoretical interpretation of the result, which could have been flawed originally, and remain flawed. And it's impossible to know when a study is not replicated why that is, whether the original was flawed or the replication effort was flawed, or even both were flawed.

This effort has been the subject of much discussion, naturally enough. In a piece published last week in The Atlantic, Ed Yong quotes several psychologists, including the project's lead author, saying that this project has been a welcome learning experience for the field. There are plans afoot to change how things are done, including pre-registration of hypotheses so that the reported results can't be cherry-picked, or increasing the size of studies to increase their power, as has been done in the field of genetics.

We'll see whether this is just a predictable wagon-circling welcome, or really means something. One has every reason to be skeptical, and wonder if these fields really are sciences in the proper sense of the term. Indeed, it's quite interesting to see genetics held up as an exemplar of good and reliable study design. After billions of dollars being spent on studies large and small of the genetics of asthma, heart disease, type 2 diabetes, obesity, hypertension, stroke, and so on, we've got not only a lot of contradictory findings, but most of what has been found are genes with small effects. And epidemiology, many of the 'omics fields, evolutionary biology, and others haven't done any better.

Why? The vagueness of the social and behavioral sciences is only part of the problem (unlike, say, force, outcome variables such as stress, aggression, crime, or intelligence are hard to consistently define, and can vary according to the instrument with which they are measured). Biomedical outcomes can be vague and hard to define as well (autism, schizophrenia, high blood pressure). We don't understand enough about how genes interact with each other or with the environment to understand complex causality.

Statistics and science
The problem may be much deeper than any of this discussion of non-replicable results suggests. First, from an evolutionary point of view, we expect organisms to be different, not replicates. This is because mutational changes (and recombination) are always making each individual organism's genotype unique and, second, the need to adapt--Darwin's central claim or observation--means that organisms have to be different so that their 'struggle for life' can occur.

We have only a general theory for this, since life is an ad hoc adaptive/evolutionary phenomenon. Far more broadly than just the behavioral or social sciences, our investigative methods are based on 'internal' comparisons (e.g., cases vs controls, various levels of blood pressure and stroke, fitness relative to different trait values) to evaluate samples against each other, rather than as representations of an externally derived, a priori theory. When we rely on statistics and p-value significance tests and probabilities and so on, we are implicitly confessing that we don't in fact really know what's going on, and all we can get are a kind of shadow of the underlying process that is cast by the differences we detect, and we detect them with generic (not to mention subjective) rather than specific criteria. We've written about these things several times in the past here.

In desperation I asked Fermi whether he was not impressed by the agreement between our calculated numbers and his measured numbers. He replied, "How many arbitrary parameters did you use for your calculations?" I thought for a moment about our cut-off procedures and said, "Four." He said, "I remember my friend Johnny von Neumann used to say, with four parameters I can fit an elephant, and with five I can make him wiggle his trunk." With that, the conversation was over. . . .

Here, parameters refers to what are more properly called 'free parameters', that is, ones not fixed in advance, but that are estimated from data. By contrast, for example, in physics the speed of light and gravitational constant are known, fixed values a priori, not estimated from data (though data were used to establish those values). We just lack such understanding in many areas of science, not just behavioral sciences.

In a sense we are using Ptolemaic tinkering to fit a theory that doesn't really fit, in the absence of a better (e.g., Copernican or Newtonian) theoretical understanding. Social and behavioral sciences are far behind the at least considerably more rigorous genetic and evolutionary sciences when the latter are done at their best (which isn't always). Like the shadows of reality seen in Plato's cave, statistical inference reflects the shadows of the reality we want to understand, but for many cultural and practical reasons we don't recognize that, or don't want to acknowledge it. The weaknesses and frangibility of our predictive 'powers' could, if properly understood by the general public, be a threat to our business and our culture doesn't reward candor when it comes to that business. The pressures (including from the pubic media, with their own agenda and interests) necessarily lead to reducing complexity to simpler models and claims far beyond what has legitimately been understood.

The problem is not just with weakly measured variables or poorly defined terms of, for example, outcomes. Nor is the problem if, when, or that people use methods wrongly. The problem is that statistical inference is based on a sample and is often retrospective, or mainly empirical and based on only rather generic theory. No matter how well chosen and rigorously defined, in these various areas (unlike much of physics and chemistry) the estimates of parameters and the like fitted to data that is necessarily about the subjects past, such as their culture or upbringing or lifestyles, but in the absence of adequate formal theory, these findings cannot be used to predict the future with knowable accuracy. That is because the same conditions can't be repeated, say, decades from now, and we don't know what future conditions will be, and so on.

Rather alarmingly, we were recently discussing this with a colleague who works in very physics- and chemistry-rigorous material science. She immediately told us that they, too, face problems in data evaluation with the number of variables they have to deal with, even under what the rest of us would enviously say were very well-controlled conditions where the assumptions of statistics--basically amounting to replicability of some underlying mathematical process--should really apply well.

So the social and related sciences may be far weaker than other fields, and should acknowledge that. But the rest of us, in various purportedly 'harder' biological, biomedical, and epidemiological sciences, are often not so much better off. Statistical methods and theory work wonderfully well when their assumptions are closely met. But there is too much out-of-the-box analytic toolware, that lures us into thinking that quick and definitive answers are possible. Those methods never promise that because what statistics does is account for repeated phenomena following the same rules, and the rule of many sciences is that, in their essence they are not following such rules.

But the lure of easy-answer statistics, and the understandable lack of deeply better ideas, perpetuates the expensive and misleading games that we are playing in many areas of science.

Wednesday, August 26, 2015

Who should take statins.....besides everyone? I thought a lot about this when I was working on a lecture about predicting disease. The purpose of statins, of course, is to prevent atherosclerotic cardiovascular disease in people at risk (how well they do this is another issue). The challenge is to identify the people 'at risk'. I wrote about this in July, but I've been playing some more with the ideas and wanted to follow up.

Statins are a class of drug that, in theory, work by lowering LDL (low-denstity lipoprotein) levels. They do this by inhibiting HMG-CoA reductase, an enzyme that has a central role in the production of cholesterol in the liver. LDL, the so-called 'bad' cholesterol, isn't actually just cholesterol, but has been linked to risk of heart disease because, as a lipoprotein, its job is to transport cholesterol to and from cells. It is bound to cholesterol. What's measured when we have our blood drawn for a cholesterol test is LDL-C, the amount of cholesterol bound to LDL particles (LDL-C), as well as HDL-C, the 'good' cholesterol package, which transports LDL-C from cells, leading to lower blood cholesterol levels. Cholesterol makes plaque and plaque lines and hardens arteries, which occludes them and leads to stroke and heart attack. Lower the amount of LDL, and you lower the risk of arterial plaque deposits.

The connection between cholesterol and heart disease was first identified in the Framingham Study in the 1950's and 60's, and this lead directly to the search for drugs to lower cholesterol. Statins were developed in the 1970's and 80's, and after some fits and starts, began to be used in earnest in the late 1980's. Statins work by inhibiting the liver cells' synthesizing of new cholesterol, that is, cholesterol that isn't due taken in in the diet.

Akira Endo, one of the first scientists to look for cholesterol-lowering compounds, reviewed the history of statins in 2010. He described the many studies of the effects of these drugs, saying "The results in all these studies have been consistent: treatment with statins lowers plasma LDL levels by 25–35% and reduces the frequency of heart attacks by 25–30%" (Akira Endo, Proc Japan Acad, Series B, 2010).

A systematic review of the literature on the effectiveness of statins was published by the Cochrane Organization in 2012. The review reports, "Of 1000 people treated with a statin for five years, 18 would avoid a major CVD event which compares well with other treatments used for preventing cardiovascular disease." This suggests, of course, that 982 people took statins with no benefit, and perhaps some risk, as statins are associated with muscle pain, slightly increased risk of type 2 diabetes, liver damage, neurological effects, digestive problems, rash and flushing, and other effects. But more on this below.

So, who should take statins?
Until 2013, the recommendation was that anyone with a modest risk, as assessed by the Framingham Risk Calculator (I've read that that means from 6.5% to 10% 10-year risk) would likely be prescribed statins. The interesting thing, to me, about this risk calculator is that it's impossible to push the risk estimate past "greater than 30%", even at maximum allowable cholesterol, LDL, and systolic blood pressure, and being a smoker on blood pressure medication. Which means that there's a lot that this calculator can't tell us about our risk of CVD, based on the best risk factors known.

In 2013, the American Heart Association/American College of Cardiology revised their criteria for statins. Now, they are recommended for people who have had one CVD event in order to prevent another; for people with primary elevations of LDL-C greater than 190mg/dL; people 45-70 years old who have diabetes and LDL-C between 70 and 189mg/dL, and people 45-70 years old with LDL-C between 70 and 189mg/dL and estimated 10-year cardiovascular disease risk of 7.5% or higher.

The first three criteria are straightforward. If statins lower LDL, and lower LDL lowers risk of ASCVD (artherosclerotic cardiovascular disease), then taking them should be beneficial. But then we're back to a risk calculator again to estimate 10-year risk.

It has been revised. Now included are ethnicity (well, White, African American or other), and diabetic status (yes/no), and estimated lifetime risk. And, now it's possible to push 10-year risk up past 70%, which I discovered by playing around with the calculator a bit. Whether or not it's a more accurate predictor of a cardiovascular event is another question.

Here's the lowest risk I could come up with, 0.1% 10-year risk. The recommendations offered are not to prescribe statins.

Lowest 10-year risk

Here's the highest risk I could force the calculator to estimate. Ten-year risk for a female with these risk factors is higher than for a male, but lifetime risk is lower. That seems strange, but ok, it must reflect association of risk factors including sex with disease at the population level.

Compared with the Framingham calculator, risk estimation seems to be getting more precise. Or at least bolder, with estimates up in the 70's. But is the new calculator actually better at predicting risk than the old one? A paper was recently published in JAMA addressing just this question ("Guideline-
Based Statin Eligibility, Coronary Artery Calcification, and Cardiovascular Events," Pursnani et al.) They identified 2435 people from the Framingham study who had never taken statins. Their medical history allowed the authors to determine that, based on the old guidelines, 14% would have been 'statin eligible' compared with 39%, based on the new 2013 guidelines.

Among those eligible by the old guidelines, 6.9% (24/348) developed CVD compared with 2.4% (50/2087) among noneligible participants (HR, 3.1; 95% CI, 1.9-5.0; P less than .001). Under the new guidelines, among those eligible for statins, 6.3% (59/941) developed incident CVD compared with only 1.0% (15/1494) among those not eligible (HR, 6.8; 95% CI, 3.8-11.9; P less than .001).

So, put a whole lot more people on statins, and you prevent an additional very small number of CVD events; 1.0% vs 2.4%. And, 93% of those ‘eligible’ for statins did not develop disease. Nor, of course, do statins prevent all disease. Actually, if everyone in the population were covered, statins would be preventing as many events as they could possibly prevent, but in a small minority of the population. That is, 90+% of people considered to be at 'high-risk' of disease don't go on to develop disease. Is it worth the side effects and cost to put so many more people on statins to prevent the 1.4% more CVD that these new guidelines are preventing? Well, heart disease is still the number one killer in rich countries, and 40+% of the population is currently taking statins, so a lot of people have decided that the benefits do outweigh the risks.

Another question, though, is more fundamental, and it concerns prediction. The calculator seems to now be predicting risk with some confidence. But, let's take a hypothetical person with a somewhat elevated risk. Her cholesterol is higher than the person above who's at lowest risk, but that's due to her HDL. Her systolic blood pressure is high at 180, which is apparently what bumps up her risk, but her 10-year risk is still not over 7.5% so the recommendation is not statins, but lifestyle and nutrition counseling. (Though, the definition of 'heart-healthy diet' keeps changing, so what to counsel this person with low risk seems a bit problematic, but ok.)

Low enough risk that statins aren't advised.

Now here's the same hypothetical person, but she's now a smoker, on medication to lower her blood pressure (and her b.p. is still high) and she has diabetes. Her 10-year risk of ASCVD jumps to 36.8%. This makes sense, given what we know about risk factors, right? The recommendation for her is high-intensity statins and lifestyle changes -- lose weight, do regular aerobic exercise, eat a heart-healthy diet, stop smoking (easy enough to say, so hard to do, which is another issue, of course, and the difficulty of changing all these behaviors is one reason that statins are so commonly prescribed).

But now I've lowered her total cholesterol by 70mg/dL, which is what statins ideally would do for her. Even so, the American College of Cardiology/American Heart Association recommendation is for 'high-intensity statin therapy' and lifestyle counseling. The calculator doesn't know this, but statins have already done everything they are likely to do for her.

So, let's add lifestyle changes. But, even when she quits smoking, her 10-year risk is 20%. So let's say we cure her diabetes -- even then, she's still at high enough risk (9%) that 'moderate to high-intensity statins' are recommended. I'm confused. I think even the calculator is confused. It seems there's a fuzzy area where statins are being recommended when what's left to do is, say, lower blood pressure, which statins won't do. This hypothetical woman probably needs to lower her weight to do that, and statins aren't going to help with that, either, but still they're recommended. Indeed, one of the criticisms of this risk calculator when it was released in 2013 was that it overestimates risk. Perhaps so, but it also seems to overestimate the benefit of statins.

Further, it seems there are a lot of type 1 errors here. That is, a lot of people are considered 'at-risk' who wouldn't actually develop cardiovascular disease. Risk of 7.5% means 7.5 of 100 people with a given, equal set of risk factors are expected to develop disease. That means that 92.5 would not. And that means that we have a pretty rough understanding of heart disease risk. The strongest risk factors we know -- smoking, high LDL-C, diabetes and hypertension -- can be expected to predict only a small fraction of events.

And that means that either something else is 'causing' cardiovascular disease in addition to these major known risk factors, or something is protecting people with these risk factors who don't go on to develop disease. Family history is a good or even the very best single predictor (why isn't it taken into account in these calculators?) which suggests that it's possible that genetic risk (or protection) is involved, but genome wide association studies haven't found genes with large effects. Of course, family history is highly conflated with environmental factors, too, so we shouldn't simply assume we need to look for genes when family history indicates risk. Anyway, it's unlikely that there are single genes responsible for ASCVD except in rare families, because that's the nature of complex diseases. Instead, many genes would be involved, but again as with most complex diseases, they would surely be interacting with environmental risk factors, and we don't yet know understand how to identify or really understand gene by environment interaction.

And then there's the truly wild card! All of these risks are based on the combinations of past exposures to measured lifestyle factors, but the mix of those and the rise of other new lifestyle factors, or the demise of past ones, means that the most fundamental of all predictors can itself not be predicted, not even in principle!

So, statins are a very broad brush, and a lot more people are being painted with them than in fact need to be. The problem is determining which people these are, but rather than zoom in with more precision, the updated calculator instead paints a whole lot more people with the brush. This isn't the calculator's fault. It's because understanding risk is difficult, ASCVD is a large and heterogeneous category, and prediction is very imprecise -- even for many 'simple' Mendelian disorders. If ASCVD were caused by a single gene, we'd say it had very low penetrance. And we'd want to understand the factors that affect its penetrance. That's the equivalent to where we are with cardiovascular disease.

I was interested to see that the 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk says something that I have said so many times that I decided not to say it again in this post. But, I'm happy to see it elsewhere now. The guideline committee itself acknowledges the issue, so I'll let them explain the problem of assessing risk as their calculator does.

By its nature, such an approach requires a platform for reliable quantitative estimation of absolute risk based on data from representative population samples. It is important to note that risk estimation is based on group averages, which are then applied to individual patients in practice. This process is admittedly imperfect; no one has 10% or 20% of a heart attack during a 10-year period. Individuals with the same estimated risk will either have or not have the event of interest, and only those patients who are destined to have an event can have their event prevented by therapy.

It's the problem of using group data, which is all we've got, to make clinical decisions about individuals. It's the meta-analysis problem -- meta-analyses compile data from many individual studies to produce a single result that certainly reflects all the studies, because they were all included in the statistics, but it doesn't represent any of them with precision. Ultimately, it's the problem that these sorts of inferences must be based on statistical analysis of samples -- collections -- of individuals. We do not have an easy way around this, including the N of 1 studies currently being proposed.

Finally, here's a meta-thought about all this. Ken and I were in Finland this month co-teaching a course, Logical Reasoning in Human Genetics, with colleagues, including Joe Terwilliger. Joe said multiple times, "We suck at finding candidate genes because we don't know anything about biology. We're infants learning to crawl." The same can be said about epidemiological risk factors for many complex diseases -- we suck at understanding the causes of these diseases, and thus we suck at prediction, because we don't really understand the biology.

Tuesday, August 25, 2015

It is well-known that the 19th century realization by Darwin and others that life evolved through historical processes rather than divine creation and intervention dealt a staggering blow to many religious believers at the time. It still does. Divine creation was a complex idea, before evolutionary theory allowed the text to be seen as a metaphorical idea, at least for biblical literalists rather than deists, who could accept that God started everything and then let it roll on by itself.

Pre-evolutionary thought
The idea of evolution can be seen in early writings in ancient classical times and in the Islamic glory years. But these were rather speculative and not what we now would call 'scientific'. Instead, it was far more obvious and natural to think of creation as static. That is, one of the important concepts of pre-evolutionary thought was permanence.

Permanence didn't mean that nothing ever changes. After all, planets move. But motion isn't the same as coming into existence anew. The problem was that God has purportedly created 'the' universe, as such, reflecting His glory in our lives. Likewise, animals and plants move and are produced, but not out of thin air, only as offspring of existing members of their kind. What was seen as not changing were the types of animals and plants--species, and the specific objects in the cosmos. These were permanent, it was widely believed, because God made it so.

Evolution suggested that basic things came into existence on their own, as it were. If that were so, then God's work would be harder to understand, or so it would seem given the biblical literalist view of things before the age of science, even into the 19th century.

The point is that 'evolution' was a threatening idea not just to the world of biology in relation to Darwin's and Wallace's work, but more generally. Or, more generally, Darwin's and Wallace's ideas flopped down amidst what was already a controversial area. This can be seen in an interesting way in an area of science that otherwise might not seem to be threatening in this way......except that "In the beginning, God created the heavens and the earth".

19th century astronomy
Astronomy is more than just star-gazing in awe of Nature's wonders. It is about the cosmos, existence itself. It was long comforting, and pretty well consistent with known facts, to think of the cosmos as centered around the Earth, with the revolving Sun to warm us, and the Music of the Spheres, the stars painted onto crystal spheres, rotating more distantly around the skies.

Galileo's use of the telescope, and work of others tracking planets (mainly, Copernicus), had started to cast doubt on some of these ideas. The moon and planets weren't perfect spheres, and orbits weren't perfect circles and the Sun was the center of the solar system. Uncomfortable facts like these did shake religious orthodoxy (in the West, at least), but they really were mainly mathematical re-ordering of the same objects. More to the point, perhaps, and vital for Isaac Newton, was that the cosmos was orderly--specified by mathematic laws laid down by God (Galileo had had similar ideas). There was absolute location and time, in space, with things moving like clockwork, following the Laws.

One exciting way to study God's work was through telescopes, which had been getting better and better, by far, than what Galileo had to work with. A famous example is what became the largest telescope in the world in 1854 for nearly a century, in Ireland, affectionately called the Rosse Leviathan. (Rosse was one of the supporters and developers) A good discussion of this subject is the BBC Radio4 program, Science Stories, July 8, 2015 edition.

Here is an image of the Leviathan:

The Rosse Leviathan, finished 1845

This was a 6-foot reflecting telescope. Among the amazing things that had been seen in the prior days of astronomy, with weaker instruments, were vague, smeary 'things'. They were called, appropriately, nebulae. What were they?

Here are two images from modern telescopy, not the mid-1800s. Let's look at the top one first.

It was indeed a big smear in earlier telescopes, as if it were a cloud of gas. If that were the case, perhaps it was condensing into a star with the aid of gravity. And if that were the case, then the stars in the heavens were not fixed at all, but could come (and perhaps go)! And in turn, that would mean that the heavens themselves were not permanent: they evolved! And then what of Genesis and its like?

But what if it's just too far away, and only looks like a smeared cloud of gas? The new telescopes began to resolve some of these objects, and to show that, in fact, they were points of light--stars--so that, whew!, the Universe was static after all! Still other nebulae were too far to resolve in that way and the debate was about whether they were, in fact, even more distant stars, or were star-forming clouds.

Spiral formations, now known as galaxies, like the bottom image, were also thought perhaps to be swirls of gas that might be condensing, until they, too were resolved as stars. But this still left others too far to resolve, or truly gaseous condensations. Only in the 20th century did light spectrographs show that some of these were, indeed, gas clouds.

We now have a consistent understanding of these various phenomena, and no longer debate whether the universe is constant in the ways religious doctrine had taught. Nobody was exactly wrong. Swirling spirals can be galaxies, but dust can swirl in as gravity pulls it together in the formation of stars. The original appearances were ambiguous and the questions about what the clouds were were legitimate. The interesting aspect is the way in which the interpretation filtered through, and affected, the broader world-views about the nature of existence. And the relevance of this to biology is (and was) clear.

When all is ready
Exobiologists muse about life elsewhere in space and to date it's no more than musing, really. But real biologists, who study actual known life on earth, were discovering many facts about life in the mid-19th century that dovetailed with issues about cosmic constancy.

Even as far back as Aristotle's time, fossils of plants and animals were known. The knowledge was fragmentary and largely ignored rather than studied scientifically, but by Darwin's time two major aspects of change had become very clear. First was geological change, on land and regarding island chains. Erosion and mountain building were becoming clear as true phenomena. This may not really have changed religious feelings if the time periods were consistent with biblical events, like the great flood. But time was becoming more and more obviously far longer than what Genesis implied.

Fossils had more ominous import. Species that used to exist, had disappeared, and new species including modern ones appeared here and there. Georges Cuvier, a believer, suggested, reasonably, that these were events of catastrophic loss but new creation, as part of the Divine plan.

However ideas about biological change and evolution were beginning to swirl. It was one thing to know that agricultural species had changed (cows gave more milk, sheep had woolier wool, grain yields rose) because of active selection by breeders. It was not clear up unil then that new species had arisen (agricultural breeding never really produced new species). But the complex of worldwide data on plants and animals and their distribution, along with fossils and the idea (from agriculture and hobby breeding) that change could be brought about by selection, were forcing a realization that the living world, like the cosmos, might not be as static as dogma held it to be.

In a sense, 'evolution' was 'ready' to be discovered, here, there, and as a more general theme. Ideas about the evolution of society (e.g., Marxism, social Darwinism) were right there with the times, too. This intellectual foment in the new sciences undoubtedly contributed to the discoveries, eventually of the vastness of space and truly gaseous precursors of stars, and of biological evolution. The discussions 'in the air' set the stage. But at the same time, the ready resistance was also primed. That is why, I think, Darwinism hit such a brick wall of resistance from so many intellectuals at the time, and why so many found these ideas so deeply disturbing.

The context of history is important to the development of new ideas, but also to the reaction to them. Often, ideas in one area of life have impact, or perceived impact, on many others, including deep beliefs about the nature of things.

I think we've now mainly settled into complete comfort with the idea of biological evolution, with no longer any rational arguments against, even if peering into the microscopic nature of genomics still yields a picture as blurry in many ways as the Rosse scope's images. This is because many aspects of genetic causation remain subtle and elusive, because life seems not as rigidly law-like as physics. As to cosmology, visual telescopes were only the beginning of a technological odyssey that has shed light onto the origins and development of the universe and has led to general acceptance of the fact of change. But this hardly diminishes the truly mind-blowing matters, light and dark, that we are learning about, or now know that we still don't know about, regarding the size and scope of the universe(s).

I need to share something about what I'll be wearing my first semester as a tenured professor.

But to get us there, I'll need to pose a string of rhetorical questions:

Tired of students rating your course according to what you wear?

Can't find a way to make the professional looks that you prefer pair with flats or sneakers or anything other than torturous high heels or other dressy shoes?

Tired of spending precious time and money on work clothes that you change out of the second you get home?

Tired of choosing between this garment made in a sweat shop and that garment made by children?

Hate suits?

Work clothes feel like a costume? Especially out-of-style ones that are too expensive to replace as trends change?

Tired of spending money on dry-cleaning and all those chemicals?

Hate the unfair fact that some faculty (like those with white hair, white privilege, or beards) can get away with comfortable and often inexpensive t-shirts, jeans, and flip-flops but others cannot or cannot take the risk to find out if they can?

If you answered yes to even one of those questions (or to related questions that didn't dawn on me to ask) then may I suggest you try wearing an academic gown to teach?

If your profession comes with its very own costume, why not take advantage of it? It's what I'm going to do starting this semester. I bought a cheap academic gown on-line and I've even started decorating it:

Kind of makes my chair look professorial, doesn't it?

I know this is tradition at a few American schools, but do any of you do this where it isn't? Anyone want to start?

Wednesday, August 12, 2015

I’m not writing this in hopes that you’ll congratulate
me. This is just meant to give readers a peek behind the curtain.

I’m writing because maybe you, or maybe someone who has sway over your career, has read an academic's blog and wondered how it would affect their chances for tenure. Or, maybe you or a colleague, your chair or department head, your dean, or your provost has wondered why anyone would bother going to the trouble to write on a blog when there are more important things to accomplish. Well, in my case, there clearly weren’t, because I managed to write on this blog and still be awarded tenure. What's more, I know, without a doubt, that my writing on this blog was integral to it.

Not me and not Proconsul.
This is the seriously awesome result of googling for "Mermaid Professor." (source)

I’ve written about why I blog before. And, looking back, there is so much more I could add to that post because of what's occurred over time since. However, the main reason still stands: Writing on The Mermaid’s
Tale has been immensely important for my academic life. The reading and writing I do here enhances my teaching and research and the enlightening
discussions I participate in here and elsewhere (facilitated by my writing here) boost my
teaching and research even more. And the people who make the decisions about my tenure definitely noticed. My departmental colleagues, my dean, and the provost all readily acknowledged the value of my blogging in their letters recommending me for tenure. And the good people who served as my external reviewers didn't see my blogging as damning enough to withhold their support. And the good... no, great people who collaborate with me certainly never turned up their noses either!

I've known since receiving the provost's letter that I owe it to readers and other bloggers to post something about getting tenure. I also thought a tenure-related post could help out younger academics, in general, by exposing how someone who's never taught in a graduate program--with all the intellectual buzz and the worker bees to help, you know, the academic model us Ph.D.s are most familiar with--can still get awarded tenure.

But I've been dreading such a post because I really don't want to write a biography right now. It feels quite narcissistic to get tenure and then to post your life story as if tenure somehow validated that, as if anyone could possibly emulate another person's detailed path to tenure, as if anyone would want to!

Plus, where to begin? So much so deep in my past has set me up for getting awarded tenure, so many people have been crucial to this outcome, that it's impossible to know where or with whom to start except, obviously, at conception.

But what I really don't feel like writing about publicly, and in association with hooray-for-tenure, is about why I haven't done much work on early Homo despite studying with a terrifically wonderful advisor, Alan Walker, to do just that. And that's because part of the reason is a statistic here. That, as well as other parts of the explanation take away from the fact that I'm very happy with the way my career has panned out and I continue to look very much forward to every single day I'm an anthropologist.

So instead of a tour through my influenced and circumstantial history leading up to tenure, maybe I'll post the narratives I included in my portfolio. It's going to be uncomfortable. I'm going to have to look away while I paste the text, like I do when the phlebotomist pricks my vein. But here you go, minus the files of evidence that go along with each narrative.* This is a successful tenure portfolio at a small state school, in an undergraduate-only program. Hope it's useful because ouch it feels quite personal:

Tenure Portfolio Narratives

Statement of Teaching and Learning
I’ve taught four different courses so far at URI and they all focus on human origins, evolution and variation. The introductory course, APG 201: Human Origins, counts as a general education requirement for the natural sciences and also is a requirement for majors and minors in anthropology. The upper level courses attract not just anthropology majors and minors but students from diverse scholarly backgrounds who are interested in the in-depth examination of issues in biological anthropology. These upper level courses include: APG 300: The Human Fossil Record (a hands-on course which is why I dedicated a large portion of my start-up funds to the purchase of new fossil casts which augmented the existing collection); APG 310: Sex and Reproduction in Our Species (a course I created because of my new research interests in the evolution of human reproduction, as well as in procreative beliefs and how they have influenced human evolution.); APG 350: Human Variation (in which I will continue to use personal genomics to engage students.). In all of these courses, my two most important teaching goals are:

(1) Students should get as strong a handle on evolution as possible, shedding as many misconceptions as possible, so that they can best comprehend the biological, ecological, and cultural significance of human variation and evolution. (That, in a nutshell, is why human evolution is taught and studied within an anthropological context!)

(2) Students should achieve as much of this evolutionary and anthropological understanding on their own as possible, by thinking creatively, synthetically, and critically about the evidence.

Number one means that I probably take more time with evolutionary theory than most of my colleagues at other institutions. But because biological anthropology is the only college-level exposure to evolution (let alone biology) that many undergraduates have, it’s important that it's strong. Once they graduate, they’re consuming, producing, and voting based in no small part on their understanding of their place in nature and their (and others') place in the human species. This one chance that we get to represent evolutionary theory and human ecology and biology is crucial make-or-break time for us anthropology professors. Number two means that I have to deviate far from the conventional format for the introductory course.

In January 2012, I was awarded a $21,842.50 from the Provost’s Office under their initiative called “Innovative Approaches Using Technology to Enhance the Student Experience at URI”. The title of my proposal, “145 URI undergraduates peer into their genomes to trace their ancestries, discover their individualities, ponder their futures, and celebrate their unified humanity,” sums up nicely what students were able to do. It has been a transformative new curriculum on many planes, from my perspective as a teacher, from student perspectives as learners, and also for the impact it is making on how my colleagues in my field and beyond will use personal genomics to teach anthropology. That is why I will continue to use personal genomics in APG 350.

I'm always updating APG 201, every semester, with new findings in human evolutionary biology and physical/biological anthropology. I'm also always modifying pedagogy and adapting activities with the goals of improving and broadening student learning. For example, I use colored index cards (in lieu of clickers) for regularly practicing questions with immediate feedback, which seem to engage and motivate students in new ways. I also used personal genomics in this course when I awarded the Provost’s grant, however, I plan to only use it in the upper level course (APG 350) in the future, not because it wasn’t a success, but because it takes up too much time away from fundamentals that need to be covered in this introductory course.

Since arriving at URI, I have dramatically rearranged the traditional presentation of APG 201 course materials (as they are presented in every major textbook for this popular Gen Ed course in North America) and have taught it for three years in this new way with great success. The major difference is that I start with active observations and then work on explaining them with evolutionary theory rather than beginning with evolutionary theory and then asking students to apply it thoughtlessly to spoon-fed information. Starting in Spring 2015, I will begin teaching it without a textbook, using two excellent popular science books and many on-line high-quality readings instead. The syllabus for this new curriculum is included in my portfolio. I will provide essential, fundamental material in handouts when it is not covered explicitly in the readings—something I’ve been poised to do since I wrote a reference/textbook Human Origins 101 in 2007. I plan to eventually publish a paper describing this new strategy of guiding who I call “naturalists in a molecular age.” Because word has gotten out to my colleagues about both the personal genomics as well as this new curriculum, I’ve been invited to participate in an education symposium (that’s been accepted) at this year’s physical anthropology meetings in March 2015.

One of the most positive outcomes of the first run of APG 310: Sex and Reproduction in Our Species was the recruitment of a student (name withheld, Anthropology and Chemistry major, class of 2014) to take on a project in APG 470: Directed Research with me, guided by constructive input from the whole class. He updated a survey from a 1960s Master’s thesis at URI that looked into “premarital sexual behavior” of undergraduates here at URI. After earning IRB approval to administer the survey to volunteer participants, he presented his research at the end of the Spring 2014 semester to a group of students and faculty. Most interesting was the result showing no significant difference in the amount of premarital sexual behavior that male and female students reported, as opposed to the significant difference between the sexes that the first survey found, decades ago. This sort of work piques student interest and two anthropology majors from my second-run of APG 310, name withheld and name withheld, have worked with original student name withheld to rewrite the survey to bring it up to date, to be more health-focused, and in hopes of making the results more instructive to the URI community. Name withheld and name withheld will be submitting their proposal to the IRB committee in October 2015 and if approved they’ll be collecting the data and analyzing it over the course of the academic year.

I have been very lucky that some of the most enthusiastic researchers and clever minds have opted to work on projects with me for credits in APG 470. I asked name withheld (Anthropology & Biology) to co-author an article on the evolution of childbirth with me for the Annual Reviews of Anthropology because of her research skills and also her relevant interests as demonstrated in prior anthropology courses with me. And then name withheld (Anthropology & Biology) has gotten a head start on her Honors project with me already. She’s taken up a project that I’ve been wanting to get started since 2006. She’s figuring out how apes lost their tails and, thus, why we ended up tailless. In the coming academic year, she’ll be applying for funding to travel to regional museums to collect data on primate skeletons.

In the next few years, I will be devising short courses and field trips through the study abroad office to sites of anthropological interest—not just to my fossil field sites in Kenya, but to other sites in Africa, Europe, and Latin America where students can chase primates in the wild or crawl into painted Paleolithic caves.

Statement of Research
How did humans become humans, how did apes? How does evolution work? And does it work differently in humans or because of humans? These are the questions that drive my research and educational endeavors. Since arriving in Fall 2011, URI has encouraged and supported my scientific and scholarly activity as I have pursued two main areas of research (below). I have also begun a book project that brings all of these things together. These three research areas should continue to challenge me and create opportunities for students for many years to come.1. Augmenting and making sense of the fossil record for ape and human evolution.
As part of an international and interdisciplinary team, funded by the Leakey Foundation and the NSF, I perform paleoanthropological fieldwork on Rusinga and Mfangano Islands in Western Kenya. Fossils from these sites represent plants and animals that lived in the early Miocene epoch (dating to about 20-18 million years ago), some of which, like the primate Proconsul, are good candidates for some of the earliest apes. Without the origin of apes, chimpanzees and humans would not have occurred. This work is not only geared toward finding more specimens of Proconsul and other primates, but we are also reconstructing the paleoenvironments in which these primates lived and evolved. Our latest paper to come of this project was published in Nature Communications this year.

Here at home, I continue to work on the functional anatomy and growth and development (ontogenetic) patterns of fossil apes like Proconsul, particularly in their feet and hindlimbs, as those traits relate to locomotion and to the ability to cling to mother during development, and over evolutionary time. It’s important to reconstruct how this fossil ape was moving about if we’re to understand how modern ape and human behavior came about. Since coming to URI I have taken advantage of our proximity to the primate skeletal collections at the American Museum of Natural History where I have gathered data on extant primates to compare against the fossils. Up until recently this work has been a continuation of my doctoral dissertation on anthropoid feet and hindlimbs, but recently I have begun a similar project with undergraduate anthropology/biology major and honors student name withheld on tails. By looking to primates in the fossil record (like the tailless Proconsul), to variation in extant primate tails, and to known genes for tail development, we are answering the question, “Why don’t humans have tails?”

Although there’s much to keep us busy in addressing these matters here in the U.S., I would still like to return semi-regularly to Kenya to continue the lifetime of work that needs to be done at Rusinga and Mfangano Islands, in both fossil collection and analysis. I hope to create a short course with International Programs to give URI students a marvelous experience doing paleoanthropology.

2. Reconstructing the evolution of human pregnancy, childbirth, and infant development
Living apes, not just fossils, also offer a glimpse of evolution. So along with another team of collaborators, I study energy use in apes and other mammals. Mammals process energy differently from one another and these differences may reflect different evolutionary selection pressures both internally within the organism and externally from the environment. Energetic use in humans is fairly well understood but it's only through comparison with other species that we can understand human energetics from an evolutionary perspective. Likewise, human data are necessary for understanding the energetic use of other primates. To this end, I’ve collected energetic and behavioral data from the chimpanzees and gorillas at Lincoln Park Zoo. The first paper to come of this work was published this year in PNAS.

I am particularly interested in the energetics and metabolic parameters of pregnancy, fetal growth, infant growth, and lactation and how those determine the timing of birth in humans and other mammals. This is a significant area of anthropological research, given how it has long been assumed that the unique human skeleton, particularly the pelvis and how it’s metamorphosed for upright walking, has limited gestation and fetal growth—that the skeleton explains why our babies are difficult to birth and are quite helpless when they arrive. My research has shown that this traditional pelvic explanation (the “obstetrical dilemma”) is much weaker than its popularity indicates and that maternal metabolism and how mothers process energy are likely to be the primary determinants of gestation length and fetal growth, not just in humans but across primates and placental mammals. Although it is my primary goal to reconstruct human evolutionary history as accurately as possible (or at least as plausibly as possible), there are also potential applications of this research toward better understanding the causes of pregnancy disorders like preeclampsia.

This research has attracted attention and I have been invited to give talks at numerous college campuses as a result. The highlight so far has been the invitation from organizers (and established human reproduction researchers) Karen Rosenberg and Wenda Trevathan to participate in a scholarly seminar at Santa Fe’s School for Advanced Research (SAR) titled “Costly but cute: How helpless babies made us human.” The collection of our papers is currently under peer-review and the volume should be published next year. I’ve also been invited to write on the evolution of childbirth for the Annual Reviews of Anthropology. That manuscript is due in January 2015 and I’ve enlisted a keen undergraduate anthropology/biology major, name withheld, to co-author the piece with me.

I am currently scheming up my next research steps. (The rest of this paragraph is redacted because it's a big fun secret for now.)

The Baby Makers: Scholarly/Popular Trade Book Project
For the last two years I’ve been working with a literary agent on a proposal for a book that I’m very excited about. It’s requiring me to scratch at the overlap between evolutionary biology and cultural anthropology—disciplines that are diametrically opposed in the eyes of many scholars. Reconciling these two schools of thought as well as discovering what, perhaps, evolutionary biology cannot explain is challenging but feels necessary in order for me to go on as both an anthropologist and an educator. The book assumes, as its premise, that ... (The rest is redacted because it's a big fun secret for now. It's a project that I've since partnered-up with Anne in, and we'll gladly talk about it but not post much about yet. We're very excited and having a ball.)

Statement of Service and Professional Outreach
I have participated in service projects at many levels at URI and within my field, while I have also prioritized outreach, locally and beyond. I will continue to perform these duties and hope to increase my contributions and impact, but here is what I have done so far:

Our department had a successful search for a new colleague and I’m proud to have been on the committee that helped to accomplish it. In addition to our regular advising majors and minors, I served as the anthropology advisor at University College for the 2013-14 academic year. The same year I joined the Faculty Senate and I served on name withheld’s Master’s committee in CELS where he defended a stellar thesis on shark feeding morphology. This year I served on the search committee for a multicultural postdoctoral fellow in BES/CELS chaired by name withheld.

Beyond URI, I have reviewed manuscripts for several scientific and scholarly journals, as well as grant proposals for NSF and the Leakey Foundation. In 2013, Nature Education launched the room of open-access, peer-reviewed articles on The Human Fossil Record, which I edited as part of their Biological Anthropology series. There are even more articles in press that will be posted soon. In addition, I was invited to give a talk at the California Academy of Sciences in November 2012 about my experience with personal genomics (23andMe) as an educator, as an anthropologist, and as a human being. While I was in San Francisco I visited an assembly of 3-8 graders as well as a high school genetics class and talked with them about science, genetics, paleoanthropology, and evolution. There, I also gave a presentation to the Leakey Foundation’s Scientific and Executive Boards about the research I’ve done that they’ve funded and will hopefully continue to support. It was well received and I was encouraged to keep applying for funding. Here in Rhode Island I have presented on evolution at a public library, a Masonic lodge, a Catholic elementary school, and three times at assisted living/retirement homes.

For the past three years I have been a core team member of the Smithsonian Institution National Museum of Natural History’s Human Origins Program Educator’s Network (HopEdNet). My duties include fielding questions about human evolution, via email, that visitors to the exhibit hall in Washington DC type into the computer. I’m also involved with the Smithsonian in a magnificent project called “Teaching Evolution Through Human Examples” (or “TetHE”) which is led by PIs name withheld and name withheld of the Smithsonian’s Human Origins Program. I have helped to create new resource activities and teaching strategies focused on human evolution for AP Biology. My primary role is as scientific content consultant but I am part of a larger group of people, including the leaders of the AP Biology standards as well as pedagogy experts, all working together on this project. These curricular packets will be complete in date withheld and I am very much looking forward to using them in APG 350: Human Variation, both to teach biological anthropology but also to expose our students to this pedagogy should they become educators themselves. It’s through my TetHE colleagues that I got my scientific process lesson plan published at Berkeley’s Understanding Science site. It’s currently one of the top three teacher resources there.

I try very hard, where and when I can, to engage the greater public in anthropology, evolution, and science and so I continue to write on the blog The Mermaid’s Tale. I write about new discoveries in biological anthropology, including my own, as well as educational issues (mainly for my colleagues), and larger “how do we know what we know” questions. This is most definitely an outreach endeavor, however, the boost to my own research and teaching that comes from writing here, and engaging with my blog’s co-authors and colleagues who read the blog, is significant. A list of my best, most popular posts is here. In total, my posts have received 110,000 hits since I began writing in 2009. Most of my posts are read by hundreds, but a few have been seen by as many as 13,000+ because some colleagues assign them to students (as do I) and others have cited or re-published them on their own websites. My most recent post on natural selection was republished by the on-line science magazine io9. Another of my posts was re-published on Scientific American’s site. It’s due in part to my activity on my blog that my anthropological research got noticed by the BBC and I was asked to be part of an episode of their science program Horizon (equivalent to our Nova). Here’s the piece in the Guardian that discusses my research and that was published to announce this television program. I also filmed all about ape and human tail loss for PBS’s “Your Inner Fish” program: “How do we know when our ancestors lost their tails?”

***
Do you have questions? Anonymous or otherwise, feel free to post here or on Facebook or Twitter and I'll do my best to answer them. Cheers.

*Here's my CV and here's my scholar.google profile. In the above narratives, you may see some new typos because I've just copied and pasted them from a pdf and also because I make typos. Hyperlinks are gone because they're not the point, and I replaced all names with "name withheld" because Google searches for those people shouldn't land on this.

Tuesday, August 11, 2015

The cost of living is ridiculous, but one nice thing about living so close to the beach (besides the beach) is that the semester begins after Labor Day. Many of our students move into vacation homes when the season ends. So although many of you are scrambling to write your syllabi for an August start, we have a bit longer to wallow in procrastination here. It's August, the Sunday of the year.

Since syllabi are on our minds, I thought I'd share mine, once again, because I've changed it, once again.

I get bored reading the same books and I'm ever-hopeful that I can improve my courses. Both of those things mean there's always serious work to be done on the teaching spectrum of this job--something that flies in the face of advice for securing tenure. But what good is that advice if teaching is valued at your institution? And what good is that advice when it's given to a lifelong learner who just cannot imagine heeding it? (I may answer these questions in an upcoming post about my path to being awarded tenure.)

Anyway, this year in APG 201: Human Origins (Introduction to Biological Anthropology; a requirement for majors and a general education course in the natural sciences), we're reading Your Inner Fish again, but we're replacing Paleofantasy with The Incredible Unlikeliness of Being. There is no textbook for good reason. And, as a bonus, students will only spend up to about 30 bucks total on materials.

Yes, I'm sort of chums with, and rather fond of, both books' authors, especially IUB's. But so what? These are fantastic books and complement beautifully not only one another but, most importantly, the material I cover in the classroom.

There will be three quizzes and a research project (focusing on information literacy) that add up to 50% of the course and a notebook that makes up the other 50%. The notebook has all the classroom notes that students take (imperative) and includes their hand-written daily assignments (yes, there are daily assignments) based on the assigned readings/viewings/activities.

Sure, it seems like a lot of grading. There are 120 students in this class, but I assure you that I am not insane. Number one: I tried the notebook experience last semester and it was hard work but it was manageable.Number two:If I can't teach at a small liberal arts college, I can still act like I do. Students deserve that experience. And so do I. The grading robots help out with the quizzes (mostly multiple-choice), but otherwise, it's up to me. I don't nit-pick with my red pen, at least not always. They just have to complete the notebook, but very thoughtfully and professionally so, to get credit. But I think it's a much much richer experience if they are encouraged to read along and to think along like this, on their own. And a great way to improve independent reading, writing, and thinking is to have them do it regularly, habitually--just like with sports. Detailed feedback or not, they will improve on these fronts just by practicing them, or they will fail the course for not doing the work. Don't come to practice, get cut from the team. It's so simple, yet so incredibly difficult for far too many with a high school diploma.

Anyway, here's the plan. If it helps you out, I'm honored. If you do something similar it would be encouraging if you could let me know (like if you use no textbook, or if you have them produce a notebook, or if you too rearrange the order of the material, which runs counter to every textbook, all of which put natural selection and genetics right up front and absolutely ruin the evolution learning experience to my mind, as I've written before). The headings for each day (see below) describe that day's lecture/discussion topic and there aren't always readings that address those specifically! I provide quite a bit of information in the form of handouts when that's the case. Also, I have more readings listed here than one might expect for an introductory level, general education course. The saying goes that students should spend three hours outside class for every hour inside class. And I agree. I also think it's a tragedy and, worse, a financial scam (some are $100k in debt... for a state school!) if they're not challenged enough to do much work outside of class. Some of the readings listed are there for students who need help understanding lecture or who missed lecture. That is, some of the readings can be skipped if students are present and engaged with lecture, which draws heavily on them. Of course, the readings that the assignments rest on cannot be skipped. And, of course, my questions based on the readings will improve each semester. Enough rambling, though. Here's the plan:

APG 201: Human origins

Unit 1. OBSERVE. This view of life. Our place in nature.

Big questions: What is the anthropological perspective? What is the scientific approach
to understanding human origins? What is a human? What are human traits? How do
humans fit on the Tree of Life? What is evolution?

1.1– Introduction to course*

*I used to do Dog Origins with my dog, as a metaphor for what we were about to do with humans, but my dog is getting too old and frail and I've got this beautiful new baby so I'm going to use my baby instead and talk about his development and theirs, etc...to set up both the books and the lectures to follow. I don't pass out the syllabus until the end of this first day. We go over it on the second day of class.

Notebook Assignment

·In-class writing assignment ("What is evolution?")

1.2 – Overview of course

Reading/viewing

·IUB,Chapter 1: Beginnings - Roberts

Notebook Assignment

·In a half-page or
more: Reflect on Roberts’ chapter and be
sure to include what it’s got to do with human evolution.

1.3 – Doing Biological Anthropology

Reading/viewing

·What is it like to
be a biological anthropologist? A Field Paleontologist's Point of View – Su (Nature
Education)

·In a half-page or
more: Reflect on Roberts’ chapter and be
sure to include what it’s got to do with human evolution.

·In a half-page or
more: Write about your primate video viewing experience, for example, you might
write about what you saw, at face value, or you might want to write about what
defied your expectations or what surprised you, or what you would like to learn
more about.

1.7 – Locomotion and encephalization

Reading/viewing

·IUB,Chapter 4: Speech and gills - Roberts

·Many primate video
clips –Posted on Sakai

Notebook Assignment

·In a half-page or
more: Reflect on Roberts’ chapter and be
sure to include what it’s got to do with human evolution.

·In a half-page or
more: Without looking at any resources except for these films, come up with
some categories for the different types of primate locomotion, give those
categories names and definitions, and list which species in the films fall into
which categories you’ve created.

·In a half-page or
more: What does Shubin mean by "your inner fish"? What's the
connection between a fish’s fin and your hand? How could you falsify
evolutionary theory?

·In a half-page or
more: Reflect on Roberts’ chapter and be
sure to include what it’s got to do with human evolution.

1.14 – Quiz 1– NOTEBOOK CHECK

Unit 2. EXPLAIN and PREDICT. Explaining the similarities and differences.
How evolution works.

Big Questions: Why are we like our parents but not exactly? Why are we like other
species but not exactly? How did human traits and human variation evolve? How
do we know what the last common ancestor (LCA) was like?

·In a half-page or
more: After reading the Shubin chapters… Is it fair to say that when you smell
something, that something is touching your brain? Why is it called the eyeless
gene if you can have it and still have eyes? How does hearing work? What does
your ear do besides hear, and how? What does drinking lots of alcohol do to
your ears?

Big Questions: How did human traits evolve? How and why do humans vary? Should we look
to our ancestors as a lifestyle guide? Are we still evolving? Why is human evolution
misunderstood and why is it controversial?

·In a half-page or
more: Why was Ota Benga brought to the U.S.? Why was Ota Benga brought to the
Bronx Zoo? Regarding issues that Ota Benga’s story raised, what do religious
and evolutionary perspectives have in common? Why doesn’t a story like Ota
Benga’s take place today?

·In a half-page or
more: Are we still evolving? Why did I ask this question?

3.13 – Building evolutionary scenarios

Notebook Assignment

·Revise your
research project essay to make it excellent

·In a half-page or
more: After re-reading the essay you wrote in class on Day 1.1 ("What is
evolution?") compose a letter to yourself highlighting what you were right
about and what you were wrong about or what was incomplete about your answer
based on what you learned this semester.

3.14 - Quiz 3

3.15 – Conclusion to course – NOTEBOOK
CHECK

Reading/viewing

·YIF, Chapter 11: The Meaning of It All – Shubin

·IUB, The Making of Us - Roberts

·Evolution reduces
the meaning of life to survival and reproduction... Is that bad? – Dunsworth
(The Mermaid’s Tale)

·In a half-page or
more: Briefly describe what you learned this semester. And, reflect on what
you're still left wondering and how you could find the answers to your
remaining questions.

·In a half-page or
more: Can an evolutionary perspective have a positive impact on someone’s life?
Explain why you answered yes or no.

Final Exam Time Slot: No final exam: Instead, discuss notebook and course with Dr. Dunsworth and receive grade in person between 8 am-noon
today in Chafee 132.

Extra credit!!! Make a time machine then go back to the start of the
semester, attend classes, take notes, read all of the things, think about all
of the things, complete the assignments, and study for the quizzes.

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